Adventures in Machine Learning

Removing Non-Breaking Spaces: A Guide for Cleaner Text

Removing Non-breaking Spaces from Text: A Guide

Have you ever come across text that contains strange characters like “xa0”? These are non-breaking spaces, which are often used in web design and publishing to maintain the formatting of text.

However, when copying and pasting text, these characters can cause problems and make it difficult to work with the text. Thankfully, there are several methods for removing non-breaking spaces from text.

In this article, we will explore these methods and help you choose the best one for your needs.

Method 1: Using unicodedata.normalize()

The first method we will explore is using the unicodedata.normalize() method to remove non-breaking spaces.

This method converts all the characters in the text to their standardized equivalents, making it easy to remove non-breaking spaces.

Unicode characters can be categorized into different categories like “spaces”, “letters”, “digits”, etc.

As the non-breaking space falls into the “space” category it can be changed into a standard space character. To use this method, your text must be in Unicode format.

Here’s an example:

import unicodedata
text = u"Helloxa0World"
# normalize the text
text = unicodedata.normalize("NFKD", text)
# remove the non-breaking space character
text = text.replace("xa0", " ")

This will output “Hello World” without any non-breaking spaces.

Method 2: Using str.replace()

Another method of removing non-breaking spaces is using the str.replace() method, which replaces all instances of a substring with a replacement string.

In this case, we can replace all instances of “xa0″ with a regular space ” “. Here’s an example:

text = "Helloxa0World"
text = text.replace("xa0", " ")

This will output the exact same string as in Method 1 – “Hello World”.

Method 3: Using str.split() and str.join()

The third method we will explore is using str.split() and str.join() methods, which can be used to split a string into a list and then join it back together without non-breaking spaces.

Here’s an example:

text = "Helloxa0World"
text = " ".join(text.split())

This code will split the string at every whitespace character, including the non-breaking space “xa0”, and then re-join the string with a regular space character. The output will again be “Hello World”.

Method 4: Using BeautifulSoup4

Finally, if you are working with web pages or HTML documents, you can use the BeautifulSoup4 module to remove non-breaking spaces.

Here’s an example of how to use it:

from bs4 import BeautifulSoup
html = '


' soup = BeautifulSoup(html, 'lxml') # get the text of the document without any non-breaking spaces text = soup.get_text(separator=' ') print(text)

This code uses BeautifulSoup4 to extract the text content from an HTML document, and passes the separator argument to get_text() to separate words by space characters.


There are plenty of ways to remove non-breaking spaces from text, depending on your specific needs. Whether you are working with plain text or HTML documents, you can use any of these methods to remove non-breaking spaces and make your text more readable and easier to work with.

In conclusion, non-breaking spaces can cause problems when working with text, but there are several methods to remove them. Using unicodedata.normalize(), str.replace(), str.split() and str.join(), and BeautifulSoup4 can all help ensure readable and workable text.

It is important to choose the best method depending on the situation. Removing non-breaking spaces is a simple yet essential process for anyone who frequently deals with text, making it more user-friendly and less cumbersome.

Therefore, knowing how to remove these spaces is crucial for effective text processing.

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